BUG: Timestamp.normalize() can overflow silently #60583
Description
Pandas version checks
- I have checked that this issue has not already been reported.
- Query:
is:issue normalize overflow
- Query:
- I have confirmed this bug exists on the latest version of pandas.
- I have confirmed this bug exists on the main branch of pandas.
Issue description
I was trying to get the minimum date, so I tried pd.Timestamp.min.normalize() before realizing that would be out of range, but what's weird is that it overflows without warning:
>>> pd.Timestamp.min Timestamp('1677-09-21 00:12:43.145224193') >>> pd.Timestamp.min.normalize() Timestamp('2262-04-11 23:34:33.709551616')For reference:
>>> pd.Timestamp.max Timestamp('2262-04-11 23:47:16.854775807')Compare that to .floor('D'), which I thought would be equivalent, but it raises:
>>> pd.Timestamp.min.floor('D') OverflowError: value too large The above exception was the direct cause of the following exception: OutOfBoundsDatetime: Cannot round 1677-09-21 00:12:43.145224193 to freq=<Day> without overflowas well as .round('D') (same error).
Sidenote: What I really wanted was .ceil('D'), which gets the first whole day:
>>> pd.Timestamp.min.ceil('D') Timestamp('1677-09-22 00:00:00')Installed Versions
INSTALLED VERSIONS ------------------ commit : d41884b2dd0823dc6288ab65d06650302e903c6b python : 3.12.8 python-bits : 64 OS : Linux OS-release : 5.4.0-202-generic Version : #222-Ubuntu SMP Fri Nov 8 14:45:04 UTC 2024 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : fr_CA.UTF-8 LOCALE : fr_CA.UTF-8 pandas : 3.0.0.dev0+1777.gd41884b2dd numpy : 2.1.0.dev0+git20240403.e59c074 dateutil : 2.9.0.post0 pip : 24.3.1 Cython : None sphinx : None IPython : 8.22.2 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : None blosc : None bottleneck : None fastparquet : None fsspec : None html5lib : None hypothesis : None gcsfs : None jinja2 : None lxml.etree : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None psycopg2 : None pymysql : None pyarrow : None pyreadstat : None pytest : None python-calamine : None pytz : 2024.1 pyxlsb : None s3fs : None scipy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlsxwriter : None zstandard : None tzdata : 2024.1 qtpy : None pyqt5 : None